October 26, 2010
/ by Enrico Montana
In the early days of the Web, search engines were touting the number of indexed pages that they held in their data stores. Quickly that number became as meaningless as the visitor counter found on nearly all the old Geocities pages of the same era. Social media is quickly following the same pattern. Twitter, alone, is estimated to generate somewhere in the ballpark of 65M tweets a day. And like search, social is transforming its questions. It is no longer about “How Much.” Rather, it is about “How Relevant.” The data that Social Media applications provide for the enterprise needs to be meaningful to make great business decisions.
Search and Social Media are converging into the next generation of Social Intelligence for the enterprise. With any successful social media platform, you need to do more than just find that one, very relevant, very specific post that you would like to identify. You are going to need to quantify that search space, discover insights within it, and aggregate it in so many different ways that the experience feels more akin to a business intelligence experience than one of traditional search. But unlike the world of most BI in the enterprise, social media comes with a massive, unstructured, unclassified data set from which to gain the insights you need.
Why do we need Search as a core capability underlying Social Intelligence programs? First and foremost, we need search because we do not know what the market will bring us on any given day. Social media does not follow the slow moving taxonomy of corporate data. It is dynamic, massive and unpredictable. Because of these properties, we need dynamic definitions to help us merge social media with our categorized internal data systems. As we learn more, participate with our communities, join conversations and evolve, our definitions and standard measures will need to evolve with us, on-demand.
Second, we will need to leverage what the Search world has already learned. Information is not defined by a set of keywords, Boolean operators or text analytics alone. Great breakthroughs in our ability to find information online came with the observation that relevance was tied to context—from the greater online world, from my history and interests, and from real world events. In social media, we are going to need advanced forms of relevance to really help measure and carve out clean spaces of information to transform into actionable insight.
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